Run
6171826

Run 6171826

Task 2079 (Supervised Classification) eucalyptus Uploaded 27-08-2017 by Jan van Rijn
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  • openml-pimp openml-python Sklearn_0.18.1.
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Flow

sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.Conditiona lImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethres hold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classif ier=sklearn.svm.classes.SVC)(1)Automatically created scikit-learn flow.
openmlstudy14.preprocessing.ConditionalImputer(2)_axis0
openmlstudy14.preprocessing.ConditionalImputer(2)_categorical_features[0, 2, 3, 4, 9]
openmlstudy14.preprocessing.ConditionalImputer(2)_copytrue
openmlstudy14.preprocessing.ConditionalImputer(2)_fill_empty0
openmlstudy14.preprocessing.ConditionalImputer(2)_missing_values"NaN"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(2)_strategy_nominal"most_frequent"
openmlstudy14.preprocessing.ConditionalImputer(2)_verbose0
sklearn.preprocessing.data.OneHotEncoder(7)_categorical_features[0, 2, 3, 4, 9]
sklearn.preprocessing.data.OneHotEncoder(7)_dtype{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing.data.OneHotEncoder(7)_handle_unknown"ignore"
sklearn.preprocessing.data.OneHotEncoder(7)_n_values"auto"
sklearn.preprocessing.data.OneHotEncoder(7)_sparsetrue
sklearn.feature_selection.variance_threshold.VarianceThreshold(4)_threshold0.0
sklearn.svm.classes.SVC(8)_C1199.9712008631038
sklearn.svm.classes.SVC(8)_cache_size200
sklearn.svm.classes.SVC(8)_class_weightnull
sklearn.svm.classes.SVC(8)_coef00.0
sklearn.svm.classes.SVC(8)_decision_function_shapenull
sklearn.svm.classes.SVC(8)_degree3
sklearn.svm.classes.SVC(8)_gamma9.08512569604657e-05
sklearn.svm.classes.SVC(8)_kernel"rbf"
sklearn.svm.classes.SVC(8)_max_iter-1
sklearn.svm.classes.SVC(8)_probabilitytrue
sklearn.svm.classes.SVC(8)_random_state22928
sklearn.svm.classes.SVC(8)_shrinkingtrue
sklearn.svm.classes.SVC(8)_tol0.0004935405573157637
sklearn.svm.classes.SVC(8)_verbosefalse

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

17 Evaluation measures

Area under ROC curve
0.8219 ± 0.0439
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.4989 ± 0.0567
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.3783 ± 0.073
Cross-validation details (10-fold Crossvalidation)
KB relative information score
227.586 ± 3.2245
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.2545 ± 0.0109
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.3132 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Number of instances
736
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.5192 ± 0.088
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.5299 ± 0.0566
Cross-validation details (10-fold Crossvalidation)
Prior entropy
2.2629
Cross-validation details (10-fold Crossvalidation)
Recall
0.5299 ± 0.0566
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.8124 ± 0.0346
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3957 ± 0.0004
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3467 ± 0.0137
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.876 ± 0.0345
Cross-validation details (10-fold Crossvalidation)